Quantitative analysis of soil erosion causative factors for susceptibility assessment in a complex watershed

Susceptibility analysis and mapping are prerequisites to sustainable land-use management and erosion prevention. Selection of appropriate erosion causative factors (CFs) is crucial in developing valid and accurate susceptibility models. However, existing literature lacks specific guidelines for its...

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Autores principales:	Taofeeq Sholagberu Abdulkadir, Raza Ul Mustafa Muhammad, Khamaruzaman Wan Yusof, Mustafa Hashim Ahmad, Saheed Adeniyi Aremu, Adel Gohari, Abdurrasheed S Abdurrasheed
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2019
Materias:	soil erosion susceptibility mapping static and dynamic causative factors hierarchical regression Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/78e5c53161914018b747fa2b2c8771b3
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spelling	oai:doaj.org-article:78e5c53161914018b747fa2b2c8771b32021-11-04T15:51:55ZQuantitative analysis of soil erosion causative factors for susceptibility assessment in a complex watershed2331-191610.1080/23311916.2019.1594506https://doaj.org/article/78e5c53161914018b747fa2b2c8771b32019-01-01T00:00:00Zhttp://dx.doi.org/10.1080/23311916.2019.1594506https://doaj.org/toc/2331-1916Susceptibility analysis and mapping are prerequisites to sustainable land-use management and erosion prevention. Selection of appropriate erosion causative factors (CFs) is crucial in developing valid and accurate susceptibility models. However, existing literature lacks specific guidelines for its selection. As such, some important dynamic CFs are often not considered in several previous studies. Thus, this study quantitatively evaluates the impacts of the addition of dynamic CFs to frequently used non-redundant static CFs in erosion susceptibility mapping using remote sensing, geographic information system (GIS) and statistical technique. Revised universal soil loss equation (RUSLE) was used to quantify soil loss and CFs’ maps for Cameron Highlands were developed in the GIS environment. The watershed was delineated, and the corresponding CFs were evaluated for each sub-watershed. The frequently used non-redundant CFs considered were lineament density, drainage density, soil erodibility, length-slope and normalized difference vegetation index. Hierarchical regression technique was adopted to evaluate the impacts of the addition of land surface temperature (LST), rainfall erosivity and soil moisture index (SMI). The results revealed that frequently used CFs accounted for 17.9% variation in soil loss. However, the successive inclusion of dynamic CFs such as LST, rainfall erosivity and SMI to the model further increased by 28.9%, 6.0% and 16.4%, respectively. This suggests that dynamic CFs, which often neglected in erosion susceptibility assessment could further increase modelling accuracy.Taofeeq Sholagberu AbdulkadirRaza Ul Mustafa MuhammadKhamaruzaman Wan YusofMustafa Hashim AhmadSaheed Adeniyi AremuAdel GohariAbdurrasheed S AbdurrasheedTaylor & Francis Grouparticlesoil erosionsusceptibility mappingstatic and dynamic causative factorshierarchical regressionEngineering (General). Civil engineering (General)TA1-2040ENCogent Engineering, Vol 6, Iss 1 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	soil erosion susceptibility mapping static and dynamic causative factors hierarchical regression Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	soil erosion susceptibility mapping static and dynamic causative factors hierarchical regression Engineering (General). Civil engineering (General) TA1-2040 Taofeeq Sholagberu Abdulkadir Raza Ul Mustafa Muhammad Khamaruzaman Wan Yusof Mustafa Hashim Ahmad Saheed Adeniyi Aremu Adel Gohari Abdurrasheed S Abdurrasheed Quantitative analysis of soil erosion causative factors for susceptibility assessment in a complex watershed
description	Susceptibility analysis and mapping are prerequisites to sustainable land-use management and erosion prevention. Selection of appropriate erosion causative factors (CFs) is crucial in developing valid and accurate susceptibility models. However, existing literature lacks specific guidelines for its selection. As such, some important dynamic CFs are often not considered in several previous studies. Thus, this study quantitatively evaluates the impacts of the addition of dynamic CFs to frequently used non-redundant static CFs in erosion susceptibility mapping using remote sensing, geographic information system (GIS) and statistical technique. Revised universal soil loss equation (RUSLE) was used to quantify soil loss and CFs’ maps for Cameron Highlands were developed in the GIS environment. The watershed was delineated, and the corresponding CFs were evaluated for each sub-watershed. The frequently used non-redundant CFs considered were lineament density, drainage density, soil erodibility, length-slope and normalized difference vegetation index. Hierarchical regression technique was adopted to evaluate the impacts of the addition of land surface temperature (LST), rainfall erosivity and soil moisture index (SMI). The results revealed that frequently used CFs accounted for 17.9% variation in soil loss. However, the successive inclusion of dynamic CFs such as LST, rainfall erosivity and SMI to the model further increased by 28.9%, 6.0% and 16.4%, respectively. This suggests that dynamic CFs, which often neglected in erosion susceptibility assessment could further increase modelling accuracy.
format	article
author	Taofeeq Sholagberu Abdulkadir Raza Ul Mustafa Muhammad Khamaruzaman Wan Yusof Mustafa Hashim Ahmad Saheed Adeniyi Aremu Adel Gohari Abdurrasheed S Abdurrasheed
author_facet	Taofeeq Sholagberu Abdulkadir Raza Ul Mustafa Muhammad Khamaruzaman Wan Yusof Mustafa Hashim Ahmad Saheed Adeniyi Aremu Adel Gohari Abdurrasheed S Abdurrasheed
author_sort	Taofeeq Sholagberu Abdulkadir
title	Quantitative analysis of soil erosion causative factors for susceptibility assessment in a complex watershed
title_short	Quantitative analysis of soil erosion causative factors for susceptibility assessment in a complex watershed
title_full	Quantitative analysis of soil erosion causative factors for susceptibility assessment in a complex watershed
title_fullStr	Quantitative analysis of soil erosion causative factors for susceptibility assessment in a complex watershed
title_full_unstemmed	Quantitative analysis of soil erosion causative factors for susceptibility assessment in a complex watershed
title_sort	quantitative analysis of soil erosion causative factors for susceptibility assessment in a complex watershed
publisher	Taylor & Francis Group
publishDate	2019
url	https://doaj.org/article/78e5c53161914018b747fa2b2c8771b3
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_version_	1718444721661018112

Quantitative analysis of soil erosion causative factors for susceptibility assessment in a complex watershed

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